An Inductive Reassessment of Acquisition Premiums and Their Performance Consequences
Type
conference paper
Date Issued
2026-08-01
Author(s)
Abstract
Acquisition premiums are commonly interpreted as evidence of managerial overpayment, yet prior research suggests they may reflect informed assessments under valuation uncertainty. We revisit acquisition pricing by applying a machine-learning–based inductive framework to 1,833 North American acquisitions (2000–2024), triangulating insights through traditional econometric regression models and long-horizon total shareholder returns (TSR). The analysis uncovers nonlinear patterns indicating that acquirers systematically pay higher premiums for targets that markets may undervalue—specifically distressed firms, low Tobin’s Q firms, and R&D-intensive firms. Crucially, TSR analyses reveal that these premiums are statistically unrelated to long-run value destruction, suggesting the market eventually validates the price paid. These findings challenge the overpayment narrative, positing that premiums often represent rational, context-dependent strategic judgments rather than behavioral bias.
Language
English (United States)
HSG Classification
not classified
Refereed
No
Subject(s)
Division(s)